How is Test Automation different from Robotic Process Automation?


Software Testing is an integral part of the application development process and it is done to ensure high quality products are delivered. Testing is done at different levels – primary development (unit testing), testing (functional testing) and at business-user level (user acceptance testing). With the application becoming more complex with integration points and focus on increasing productivity, significant number of regression test cases are automated today. This is done to alleviate the cost of executing regression test cases. The idea is not only to reduce the cost but also to increase the accuracy and reduce the number of defects in the product.

Robotic Process Automation (RPA) tools focus on automating business processes to increase productivity, improve efficiency among others. Test Automation was done with a completely different set of testing tools and frameworks until now.

In this article, we will try to find out if RPA and Test Automation are the same or different and if a tester can derive the best out of them both. We will also explore in which phase of Test Automation does RPA fit in? And if AI component of RPA helps in testing.

Is Test Automation a subset of RPA or both are completely different domains? In what phase of Testing and Test Automation does RPA fit in?

Primary business use case targeted by both Test Automation and RPA tools is performing a series of steps on an Application without any user intervention. Steps on application can be performed either at UI level or API level or even at OS event level, which can be achieved by both Test Automation and RPA tool. Albeit, in a Test Automation tool we have to integrate several different frameworks to support UI / API / OS level automation. RPA tools such as AssistEdge provide an integrated one common IDE to perform all.

However, the business purpose of Test Automation and RPA is different. While Test Automation primarily focuses on simulating User Interaction on application under test, checking system output with expected outcome and tries to reduce number of Test Case to be run manually, RPA primarily focus on automating enterprise business process and enabling enterprise achieve increase in productivity. RPA tools such as AssistEdge also help the organization to identify the business processes to automate in order to save cost. In case of Test Automation suite of Test Cases to be automated have to be manually identified by a Test Engineer before he can create Automation script to automate the same.

As a Test Engineer, I would want my Test Automation tool to have features that enable me to do the following:

Do RPA tools have all these features?

For most of the questions above, the answer is yes. While there is a slight deviation from the target audience and business purpose, yet the major RPA players are repurposing Process configuration/Automation engine/reporting framework provided by the RPA tools to support the testing community. This is definitely a win-win situation wherein Testing community gets all the features blended in one product.

While considering different phases of testing, RPA tools probably have none or very little role to play in Automated Unit Testing where unit test cases are written by the development teams to check their piece of code. RPA tools however can play a major role in automation of Functional/Regression and UAT test cases where emphasis is more on user interaction simulation.

The below diagram depicts what RPA and Test Automation share in common in terms of functionality. And how they differ in terms of business purpose and components they possess.

It is clear from the diagram that Robotic Process Automation and Test Automation have application automation in common, however with a different business purpose. And both can be used to complement each other for achieving the desired business objectives.

How can the AI component in RPA augment testing and help testers to discover more relevant test cases?

The first step in Test Automation is to identify the set of Test Cases to automate. And this is where a Test Automation Engineer needs help in identifying the hidden random Test cases that got missed but can identify a potential defect. It is mainly to do with extrapolating but with recent developments in AI; many organizations are trying to create ML models that can identify set of Test Cases for a given application.

Major RPA tools such as AssistEdge have an in-built AI module on which ML models can be built to achieve the desired use case. RPA tools are already helping enterprises to identify business process to automate. Apart from functional test case, ML models can also be built to suggest suitable infrastructure for a given payload, re-adjust runtime configuration based on incoming payload, give alert for any potential security threat that can give a whole new dimension to how RPA can augment Software Testing.


Both RPA and Test Automation tools offer scalable and resilient automation to the end-users. The areas in which RPA can strengthen the Test Automation process is the test case Identification. This can be done through Automated test case discovery, automation scripts creation with minimal coding, parallel script execution for testing in multiple environment and finally identifying defects post test case execution.

Leading RPA players such as AssistEdge offer test modules integrated with the RPA platform. This enables the test engineers to carry out test case management effectively, configure test scripts across any application technology in a single flow, create a test framework with reusable component that can be shared across test automation teams, effectively manage the test suite run and quickly analyze the test results.

This further enables Test Automation teams to create a robust Test Automation suite and deliver high quality software.

Time & Tide wait for none; neither should businesses – Be COVID Ready with Remote Work

For a business to not get impacted during unprecedented times such as COVID-19, it requires an innovative and robust solution. No one expected COVID-19 to throw BAU activities out-of-track. Flights, trains, personal vehicles, contact centers, everything came to a standstill, barring a few organizations that had a smart Business Continuity Plan in place.

The COVID-19 pandemic has underscored the old saying — nothing is more precious than human life; However, for life to continue like before, certain businesses such as banking, hospitals, telecom, food, power, and pharma must go on.

Educational institutions, medical centers, and FMCG banks, among others, are relying on an on-premise operation to run classes, consult patients, place purchase orders, or approve invoices and approve credit applications, respectively. The lockdown has led to the suspension of critical services, thus obscuring the reality to both customers and businesses.

How can businesses continue without any interruption in these challenging times? Is it possible to maintain the scale of operations? How can one be released of mundane tasks to give precedence to human life? All these incessant questions have disturbed private and public organizations, looking for a reliable solution that can offer uninterrupted BAU experience.

Leveraging Intelligent Automation for Business Continuity

Automation has never been this critical. With 5G connectivity making inroads, the remote business seems more tangible and acceptable. A recent study by HBS stated that trust-based culture and higher productivity would be a few of the outcomes of social isolation due to reliance on technology during the lockdown. Remote working tools such as Slack, WebEx, Teams, and Zoom have seen never-before adoption rates (with Teams taking maintenance downtime).

While these tools have been in use for a long, assisting remote work operations, enterprises were challenged by disconnected activities that demanded constant human presence, operating out of legacy applications or a secure environment. Processes such as 4 Eye sign-off, invoice approval & disbursement, and transaction reconciliation required staff to be available round-the-clock working out of company premises.

Few business leaders, who have been keeping abreast with Intelligent Automation (IA), have adopted Robotic Process Automation (RPA) to not only better define their BCP (Business Continuity Plan), but also to scale their operations.

RPA, with its low-code automation platform and hyper-automation capability, applies native Artificial Intelligence capability to discover business processes, automate them and orchestrate using a cohesive platform. A thin client-based orchestrator lets process owners, on their handheld devices, remotely monitor and control digital workers running the enterprise processes.

Focused on reducing the automation cycle and increasing the scale of operations, specific ready-to-deploy skills can be accessed from the Marketplace, that let businesses immediately kick-off their RPA journey. Among these skills, Digital Workers pre-trained in business operations such as invoice reconciliation, talent management on SAP, productivity management on O-365, and client management via CRM tool Salesforce let businesses realize the key benefits of automation in a shorter timeframe. Once the solution is deployed, the day-to-day operations that must continue uninterrupted at office premises or behind a secure environment such as Citrix can run without any human intervention.

Automation Singularity- The future of productive workforce

A controversial report by BCG predicts that the lockdown, resulting from social isolation mandate, may continue for an extended period, leaving many individual contributors overwhelmed by the pipeline of outstanding tasks. A readily accessible personal assistant that could run non-stop to address scheduled demand is the need of the hour.

Enterprise Personal Digital Workers are integrated/built-in to certain applications or installed on personal machines to reduce the workload of regular asks and are available 24×7 to run without any assistance.

Never before have health and hygiene been this important. While social distancing may help flatten the COVID-19 curve, driverless vehicles, contactless store purchases, or real-time traffic management have made a strong point that — Artificial Intelligence, with constant feedback and on-demand assistance from human — will drive Automation Singularity.

Automation Singularity defines a state wherein human specialists drive customer orientation using their creativity and empathy and are complemented by digital workers with extreme productivity and consistency. The feedback mechanism and monitoring can happen remotely, driving excellence in automation.

AssistEdge has been running non-stop critical operations at global enterprises in pharma, telecom, and manufacturing with a scale of 500+ unattended digital workers in a single environment.

EdgeVerve, with its 300+ enterprise clients, and values inherited from Infosys, offers free AssistEdge licenses to ensure BAU continues, while human lives stay secure in these challenging times.

With free access to AssistEdge Academy and an active community forum engaging 10,000+ RPA enthusiasts, citizen developers can now learn and automate their critical processes while maintaining social distancing.

Achieve Efficiency, Effectiveness & Experience with Core Collections platform and Artificial Intelligence

The bottom line is that technology providers should help Financial Institutions in making AI consumption easy by leveraging plug and play AI applications, which is not a heavy investment. Let us go through one such example of how the Collections ecosystem in Financial Institutions can be a perfect candidate where AI consumption is made easier.

Efficiency & Effectiveness with integrated core collections platform

In APAC markets, we see a lot of instances where various Financial Institutions have multiple collections platform for different assets and portfolios, and different geographies and markets. This makes the collections process cumbersome leading to high operating costs across the collection’s lifecycle.

What if these financial institutions have one integrated core collections platform that supports end-to-end collections processes, powered by Artificial Intelligence and Machine Learning capabilities across multiple asset classes and loan types. This will enable them with a single view of the customer leading to:

AI amplifying the experience

Integrated core collections platform enables a single view of the customer to the lending enterprises, providing easy access to data. However, they need insights into this data to make intelligent business decisions related to their collection strategies, from the best time to connect with defaulter to the best channel to utilize. There is a far greater need to move from siloed data sets and point analytics to generating insights across a customer’s journey. As we know, a customer’s journey in a bank is across different value chains – lending value chain, card value chain, deposits value chain, and an enterprise’s procurement value chain. Using advanced AI/ML analytics in different parts of the customer’s journey generates near-real-time data that can help drive insights and translate some of those insights into action. This is what truly encompasses a Cognitive Connected Value Chain.

A combination of AI-powered Core Collections platform can deliver below values for Financial Services enterprises:

How can an Integrated Core Collections platform with AI on top of it help build business resilience?

Post COVID-19 impact, lending organizations are offering loan extensions/moratorium and deferred payment options, resulting in significant increase in collection volumes and pressure to maintain customer experience, all the while being efficient in providing assistance programs.
It’s certainly a time to adopt more intelligent platforms to sail through the rough times; typically, a significant headwind is expected post-closure of the moratorium in various countries. Below is a quick snapshot of the expected challenges and how AI & ML platforms will be effective.

This is where FinXEdge suite powers both Core Collections and Artificial Intelligence & Machine learning capabilities to make debt collections intelligent and effective. While the core collection gives organizations a power of transaction system to be used across the internal and external users in the collections ecosystem, FinXEdge Collect acts as a brain and optimizes the efforts and spend in the collections process.

In short, both integrated core platform embedded with AI helps ensure business continuity and resilience in the face of the current crisis, preparing the financial services industry to gear up to a new reality. It breaks down siloes and empowers businesses to use data to identify new opportunities. Such integrated solutions help financial institutions manage debt collections by leveraging massive volumes of data, improving efficiencies, and enhancing customer experience.

Ensuring success on automation singularity journey

The RPA narrative is slowly and steadily settling down.
The industry is graduating from debates on software bots vs humans to deterministic vs cognitive skills of bots. There is a concentrated effort to create a holistic automation strategy covering humans and digital workers and move towards automation singularity. Automation is at the center-stage in board room discussions to drive business acceleration, improve customer experience, and make informed decisions with connected insights. A recent analyst study also reconfirmed that organizations that had invested in automation tools felt better positioned to handle the COVID crisis. In all of this, one thing is sure that the “bots” (aka digital workers) have arrived and are here to stay.

Mélange of digital workforce adoption

Digital workers can take multiple shapes and forms based on business context and automation needs. In its simplest avatar, the digital worker could be a personal assistant to an SME creating daily reports or responding to templatized emails, etc. The complex reincarnations could be digital workers controlling mission-critical systems directly impacting human lives. In addition to process complexity, automation also has to conform to enterprise-grade features like security, compliance, data privacy, reliability, scalability, etc.

Furthermore, operationally some organizations are run via Automation Center of Excellence groups that govern organization-wide deployments and guide automation processes that make their way to production. Other organizations have successfully democratized automation initiatives and have individual departments/business units/geo locations run their automation programs so long as the enterprise concerns like security, compliance, etc. are demonstrated to be in control. There are also success stories of smaller micro-groups in organizations directly using Digital Workers and bringing business process improvements and increasing human user efficiency and effectiveness.

The shape and size of digital worker adoption are thus too vast and varied and no one size fits all.

Setting up successful automation

Despite the diversity, fundamentally four areas define the success of automation programs – Strategy, Sponsorship, People, and Platform. On one hand a good strategy and executive sponsorship helps set-up successful automation programs; and on the other hand skilled people and robust platforms help run the automation programs successfully. There is a lot more going beyond these pillars as well, but the strength (or lack) of these four often dictates the quality and longevity of automation programs in different enterprises.

Each of the above focus areas is nuanced, the right fit definitions are contextual and depend on the size, state, culture, and IT landscape of the target organization. As an enterprise trying to raise the bar on automation adoption, there should be a concentrated effort to give topmost priority to these areas.

Strategy – The focus should be on enabling customer-centric agile implementations and behavior in the organization, utilizing the power of the digital workforce. While RPA tools are quick and easy and have a short cycle time, the strategy should focus on the long-term journey. There should be an adequate emphasis on data-based measurements of automation in action and a robust empirical model-based derivation of automation opportunities.

Sponsorship- Like all other enterprise initiatives, successful automation programs also need the right level of sponsorship to allow programs to find the right balance in each context. This is critical not only to cover costs but also to isolate programs from unforeseen challenges and setbacks. Quite often, RPA programs get stuck after initial implementations due to incorrect prioritization of business processes for automation. Having the right level of sponsorship ensures that the team re-group, learn from the current challenges, and continue chasing the larger automation goals.

People – In the early days, the RPA narrative focused on taking away work from a human. So, it may sound a bit ironic, but humans are the backbone of running successful digital workers. The right set of SMEs who understand the business and all its primary and alternate flows go a long way in setting up successful automation programs. The end game of automation singularity is also about empowering people to work together with digital workers and be more customer-centric in their business.

Platform – Choosing the platform that handles enterprise concerns regarding scale, security and reliability is paramount to success. A platform that runs reliably every time, both in normal conditions and during peak business loads; and ensures compliance to legal and security requirements, goes a long way in building confidence towards taking higher goals on an automation journey.

In short

Each of the focus areas above is equally critical, and focusing only on one or a couple of them is never enough. These areas set a solid foundation to begin the automation exercise in your organization and help you make the most of your investment, as you progress in the automation journey. In almost all AssistEdge automation success case studies, it is evident that organizations that paid equal attention to all the focus areas are the ones who reaped good returns on their investments. So, as an organization whether you are a pioneer in your industry in automation implementations or have just onboarded the automation journey, keeping track of the above four focus areas will help you carve a successful automation story.

Leveraging Process Discovery for Workload Management

Most large enterprises operating globally have a huge number of processes across all the functions. Digitization and process automation are key initiatives taken to reduce the cost of operations and also to meet the SLAs. It is important to understand and choose the right processes for automation and get the benefits and savings as per the goals set. The Chief Automation Officer (CAO) is responsible and accountable for driving the Automation programs successfully. He has the challenge to get the ROI fast and show the benefits of automation to the management. However, to realize the benefits of automation, apart from the prioritization of the processes, the critical requirement is also on the workload management of the digital workers.

How does process discovery help in workload management?

The first step towards workload management is identifying and prioritizing high-value tasks and processes which can be taken up for automation. The expectation is to run this tool across processes and figure out the Manual Operations Index (MOI) as we call it. The MOI for each process is calculated by calibrating 30 steps and measuring the manual efforts. For example, a process with 30 steps has 15 manual steps then the MOI (Total Steps / Manual Steps) is 2.0. A process with MOI > 1.5 qualifies for Automation. Process Transaction Index (PTI) is the transaction volume for a particular process. The PTI gives the cost-benefit analysis for a process to be automated. The Range of PTI is between 1 to 80,000 per day. For example, a process having a volume of 300 transactions per day with an execution time of 30 secs per transaction, it has a PTI of 9000.

While the designs are required to consider the MOI and PTI, it also depends on the target application’s execution and response speed on which the processes are running. For example, the SAP application is one of the target applications from where the data is fetched and updated, and if that is running on slow computing infrastructure, then the maximum robot efficiency will be restricted by the underneath SAP application. Based on the MOI and PTI, the design has to take into account the number of profiles to be used for robots, which drives the number of robots required. RPA products that support multi-skilled robot usage, are easy for optimization and maximize the utilization of robot licenses purchased.

The selection of processes is a key requirement for planning automation of processes. The CAO must work on the plan with all the parameters to achieve his goals.

Process Discovery tools such as AssistEdge Discover help in process mining resulting in prioritizing tasks leading to workload management.

How an American corporation & a global healthcare company based in Europe leveraged AssistEdge Discover for workload management – A case study

There are some excellent case studies where enterprises were able to leverage the AssistEdge Discover and realize the ROI fast. AE Discover is AI-enabled and uses Machine Learning for process discovery.

One of the clients, an American corporation manufacturing agriculture, construction, lawn care, and forestry machinery, leveraged AssistEdge Discover and RPA. The client wanted an outcome-based deal and EdgeVerve successfully delivered the automation benefits to the client using AssistEdge Discover, RPA, and Engage products.

EdgeVerve has successfully implemented the AaaS model for the outcome-based deal with significant savings delivered within 6 months – automating 22 complex processes across the supply chain, finance, and loan processes giving an annual savings of $ 2 Mn, which is 60 FTEs savings. The plan is to provide an annual savings of $ 15 Mn with 200+ processes automated. The Automation Factory concept applied helps in continuously churning out automation processes in a highly optimal way.

Similarly, EdgeVerve has also successfully delivered RPA at scale automating 200+ processes for a global health technology leader in Europe operating in 100+ countries. The processes are Finance and Accounting processes which were automated in the first phase, giving almost $40+Mn savings to date, with 200+ automation use cases, using 500+ bots.


To enable workload management of the digital workforce, it is very important to categorize the processes into complex, moderate, and simple complexity in conjuncture with business criticality. Once the processes are categorized, the MOI and PTI are applied for prioritizing the processes. As part of the Automation Center of Excellence, EdgeVerve has laid very standard processes to ensure Workload Management and process prioritization. There is also monitoring of processes after automation, to further optimize the same. My recommendation is, enterprises must embark on the Automation journey and use all the industry-standard tools like Process mining, process discovery, RPA, and Engage for getting the maximum ROI in a short period. The enterprises that go with the structured approach to Automation, benefit more, and grow much faster than their peers.

Reimagining Supply Chain Efficiency with Intelligent Automation

Mr. Peter Crawley has been closely monitoring the developments globally since COVID-19 was declared a pandemic. Being the Chief Supply Chain Officer in a large retail enterprise with operations across the globe, Peter’s team has been working 24×7 to ensure seamless operations. Just like Peter’s organization, most enterprises today are facing challenges to stay afloat. In these testing times, the supply chain is being looked at to keep the operations running across industries like retail and manufacturing. These industries are completely dependent on the supply chain to keep their upstream and downstream operations afloat. To cater to the dynamic needs of these industries, the supply chain organizations should focus on combining agility, flexibility, and cost-efficiency with rapid product and service development1.

A survey conducted by Deloitte2 confirms the intent of enterprises in this direction. When Deloitte asked the respondents, “What functions are you prioritizing for future digital investment?” the supply chain emerged as the top overall answer, with 62 percent respondents choosing it over planning, product design, and smart factories.

Intelligent Automation is one such pillar helping the supply chain industry and functions achieve this by expanding the automation horizon. The focus on high accuracy levels and efficiency in operations make intelligent automation the key to this transformational change. Forrester has also called out the importance of Intelligent Automation (RPA+AI) as an important driving force to own the future of work3. In this article, we are looking at some of the key Intelligent Automation (IA) technologies that are reshaping the supply chain industry and its operations. We will also look at how the adoption of these IA technologies is redefining the role of knowledge workers across the Supply Chain industry.

The above examples give a glimpse of the endless capabilities for Supply Chain by deploying the right Intelligent Automation technologies across appropriate use cases. Let us look at the impact on Supply Chain with the advent of Intelligent Automation.

For a shipping company, operating across 139 countries on multiple systems and interfaces, EdgeVerve deployed over 400 AssistEdge RPA bots to offer price quotes and booking management within minutes as opposed to the previous 24-hour lead time.

Another US-Based company ensured business continuity in the wake of COVID-19 pandemic using AssistEdge RPA’s Intelligent Automation capabilities4. This transportation and logistics company operating in 30 countries, wanted to ensure that payment operations are on track, and payments processing can be done remotely and in a more agile manner. The solution helped them better manage the orders into Ready-to-bill (RTB) and ready-to-pay (RTP) status, resulting in a reduced Annual Daily Sales Outstanding of USD 2.5 M.

There are numerous other examples where supply chain organizations are already reaping the benefits of deploying Intelligent Automation capabilities across their processes. You can also take up similar initiatives by creating a core team that focuses on identifying the right use cases and assisted by a Process Discovery tool. They should look at the profiles of different knowledge workers, identify the areas which are best suited for specific IA technologies, and reimagine the supply chain.


1 Automation Singularity –

2 Deloitte Industry 4.0 Investment Survey 2018 –

3 Forrester Report – Embrace Six Success Drivers to Own The Future Of Work by Craig Le Clair

4 Stronger Together: AssistEdge RPA automated billing process for a global logistics provider during COVID-19 crisis –